DIFASTERS AND REGIONAL RISKS OF DEBRIS FLOW IN ZHAOTONG PREFECTURE，YUNNAN PROVINCE，CHINA

（刘希林）ＤＩＦＡＳＴＥＲＳＡＮＤＲＥＧＩＯＮＡＬＲＩＳＫＳＯＦＤＥＢＲＩＳＦＬＯＷＩＮＺＨＡＯＴＯＮＧＰＲＥＦＥＣＴＵＲＥ，ＹＵＮＮＡＮＰＲＯＶＩＮＣＥ，ＣＨＩＮＡ￥ＬｉｕＸｉｌｉｎ（ＩｎｓｔｉｔｕｔｅｏｆＭｏｕｎｔａｉｎＤｉｓａｓｔｅｒａｎｄＥｎ...     

Dynamic characteristics and hazard assessment of debris flow in Shangyao valley

Shangyao valley is located in Jin’an village of Songpan in Sichuan. Many material sources are accumulated in valleys. The debris flow will be triggered by a rain storm with short-duration and strong intensity, which may threaten people’s lives and property in downstream. Based on the investigation,the formation conditions of debris flow and its dynamic characteristics are analyzed and its hazard assessment is investigated. Research shows that there is the potential cause of debris flow in Shangyao valley,which is of the middle risk class.     

Uncertainty analysis on zonation maps of debris flow hazard in Yunnan Province, China

lINTRODUCTIONDebrisflowisoneofthesixprimarynaturalhaz-ards,whichinfluencesthedevelopmentofnationalso-cietyandeconomyinChina.Itsseverityissecondarytoflood,draught,earthquake,typhoon,butstrongerthanbiologicalhazards.Morethan3ooOodebrisflowcreeksarescatteredihthewholemountainousarea,andes-PeciallyconcentratedinsouthwestofChina.DebrisFlowInformationSystem(DFIS)operatedbytheInsti-tuteofMountainHazardsandEnvironmentoftheChi-neseAcademyofScienceshasalreadyestablishedadatabaseandcataloguec…     

THE ORIGIN AND CHARACTERISTICS OF THE GLACIAL DEBRIS FLOW IN THE DUKU HIGHWAY OF TIANSHAN MOUNTAINS，

ＴＨＥＯＲＩＧＩＮＡＮＤＣＨＡＲＡＣＴＥＲＩＳＴＩＣＳＯＦＴＨＥＧＬＡＣＩＡＬＤＥＢＲＩＳＦＬＯＷＩＮＴＨＥＤＵＫＵＨＩＧＨＷＡＹＯＦＴＩＡＮＳＨＡＮＭＯＵＮＴＡＩＮＳ，ＣＨＩＮＡ￥ＸｉｏｎｇＨｅｉｇａｎｇ（ＤｅｐａｒｔｍｅｎｔｏｆＧｅｏｇｒａｐｈｙ...     

Disasters and regional risks of debris flow in Zhaotong Prefecture,Yunnan Province,China

Zhaotong Prefecture has the area of 22,434km², where there are more than 330 debris flow ravines, with the average spatial density of 14.7 spots per 1,000km². According to the method of evaluation on the regional risk of debris flow, this study has come to the following conclusions: Qiaojia County-risk grade V; Yongshan, Yanjin, Ludian, Daguan, Weixin and Zhenxiong counties-risk grade III; Yiliang, Suijiang-Shuifu and Zhaotong City-risk grade II. Compared with the field investigation, the result is satisfied.     

Sedimentary macro-structures and forming mechanism of debris flow

IIWr~IOWThesedimentarycharacteristicsofdebrisflowcanreflectthecompoSition,fluidtypeandsedimentaryprocess.ThescholarswhostudymoderndebrisfloWinChinagenerallyclassifydebrisflowbythemethodofviscositywithfloWpattern.SeveraltypicalschemesareshowninTable1,inwhichthemethodofunitweight(fluiddensityinunitvolumet/m3)isusedandfluidunitweightisthoughttobethedirectproPOSitiontotheviscosityofdebrisflow(Wu,1990).Ithasbeenprovedbyhydrcrmechacsthatnon-cohesivedebrisf1OwfollowsBagnoldgranular'flowmedel(B…     

Characteristics of Large Low-frequency Debris Flow Hazards and Mitigation Strategies

A low-frequency debris flow took place in the north coastal range of Venezuela on Dec. 16, 1999,and scientists all over the world paid attention to this catastrophe. Four characteristics of low-frequency debris hazard are discussed: long return period and extreme catastrophe, special rare triggering factors,difficulty in distinguishing and a series of small hazards subsequent to the catastrophe. Different measures, such as preventing, forecast - warning,engineering, can be used for mitigating and controlling the catastrophe. In engineering practice, it is a key that large silt-trap dams are used to control rare large debris flow. A kind of low dam with cheap cost can be used to replace high dam in developing countries. A planning for controlling debris flow hazard in Cerro Grande stream of Venezuela is presented at the end of this paper.     

RECENT DEVELOPMENTS IN DEBRIS FLOW RESEARCH IN ITALY

ＲＥＣＥＮＴＤＥＶＥＬＯＰＭＥＮＴＳＩＮＤＥＢＲＩＳＦＬＯＷＲＥＳＥＡＲＣＨＩＮＩＴＡＬＹＭａｒｃｈｉＬｏｒｅｎｚｏ；ＴｅｃｃａＰｉａＲ．（ＩｎｓｔｉｔｕｔｅｆｏｒＰｒｅｖｅｎｔｉｏｎｏｆＨｙｄｒｏｌｏｇｉｃａｌａｎｄＧｅｏｌｏｇｉｃａｌＨａｚａｒｄ...     

Annual precipitation gray forecast in disaster year of Chedaren debris flow

The Chedaren ravine belongs to high-prone areas of debris flow in Jilin Province,which threaten the local people's life and security seriously. The authors used the residual correction theory to amend the GM (1, 1) model and forecast annual precipitation in disaster year of the Chedaren ravine; it provides scientific foundation for early warning of debris flow disaster in the rainy season based on weather forecast. The prediction results show that annual precipitation is 724.7 mm in 2009; the region will probably occur large-scale debris flow during the rainy season.     

Annual precipitation gray forecast in disaster year of Chedaren debris flow

The Chedaren ravine belongs to high-prone areas of debris flow in Jilin Province, which threaten the local people＇ s life and security seriously. The authors used the residual correction theory to amend the GM （ 1, 1 ） model and forecast annual precipitation in disaster year of the Chedaren ravine ; it provides scientific foundation for early warning of debris flow disaster in the rainy season based on weather forecast. The prediction resuits show that annual precipitation is 724.7 mm in 2009 ; the region will probably occur large-scale debris flow during the rainy season.     

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.